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Project exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).
Proper citation: The Cancer Genome Atlas (RRID:SCR_003193) Copy
CCPRB (Cancer Control using Population-based Registries and Biobanks) is a Network of Excellence project within the sixth framework programme of the European Union. It is aiming at improved control of cancer by facilitating research linking biobanks and cancer registries. The project involves a systematic quality assurance and continuous development of standards and norms for human sample biobanks in Europe, as well as development of improved integrity-protection standards in the handling of sensitive information in connection with biobank-based research. The samples in the biobanks will be used in large-scale cancer research searching for genetic and infectious causes to cancer, in particular in the areas of breast and colorectal cancer and childhood leukemia. Project objectives: * Provide the study base for uniquely large population-based prospective studies on cancer * Define and implement a generally applicable European Quality Standard for Biobanking that will include improved data and specimen standardization, acquisition and analysis, reliable and standardized statistical analysis as well as improved management and co-ordination of European biobanks. * Define and promote the implementation of integrity-proof methods for biobank-based research involving well defined and secure third party code-keeping systems. * Enable large-scale, population-based research on: ** evaluation of cancer treatment and role of molecular markers in treatment selection ** use over-generation registry linkages applied to large biobank cohorts to identify and evaluate genetic predisposition associated with increased cancer risk as well as interactions with common environmental exposures. ** use over-generation registry linkages applied to large biobank cohorts to explore and evaluate intrauterine exposures associated with increased cancer risk ** exploit the power of large population cohorts for design of optimal strategies for cancer prevention and its evaluation. * Establish a Europe-wide network for spreading the awareness of i) the data, samples and knowledge generated European biobank-based research ii) possibilities for future biobank-based research and iii) the best practice quality standards for biobank-based research.
Proper citation: Cancer Control using Population-based Registries and Biobanks (RRID:SCR_004902) Copy
The foundation biobank-suisse (BBS) is a collaborative network of existing and future research biobanks in Switzerland. The primary goals are: 1. to provide researchers a quick overview of available human biospecimens (by using the web query interface) and up to date person related data; and 2. to provide biobankers with services to further improve the quality of biobanks in Switzerland (e.g. information about up-to-date IT and database software for biobanking; solutions for ethical, legal, and social issues; develop common platform for biobankers; etc.). We maintain a database with data about patients and biospecimens. The database can be queried from our web-site. Once the researcher has found suitable biospecimens we will bring him in contact with the biobanks, which have collected the biospecimen. The researcher and the biobank manager will then discuss the next step without further participation of the foundation biobank-suisse. We provide advice and support to biobank manager, who are in the process to start a biobanking activity for material from humans. Well established biobanks can benefit from our help in realizing specific projects to improve their operations. BBS was founded in December 2005 as an initiative of Oncosuisse and SWISS BRIDGE with the goal to build a collaborative network of existing and future biobanks for research in Switzerland. BBS has currently information from about 60 000 biospecimens and 10 000 patients. This information is provided by the biobanks shown under the Partner biobank menu item and include: * Institut de Pathologie, Centre hospitalier universitaire vaudois (CHUV) * Institut f��r Pathologie Universit��tsspital Basel * Institut f��r Pathologie der Universit��t Bern BBS has entered in a closed collaboration with SAKK''s (Swiss Working Group on Clinical Cancer Research) IT department. BBS''s server is run by SAKK and technical support is provided by the SAKK IT department. BBS is an active member of ISBER (International Society of Biological and Environmental Repositories) the international society of biobanks. BBS also joint BBMRI (an European initiative to build an pan-European network of biobanks.
Proper citation: Biobank Suisse (RRID:SCR_004935) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented on October 6, 2011. A project to collect, store and study DNA samples from tens of thousands of healthy volunteers and patients with diseases of major public importance. It aims to identify genes that are risk factors for the conditions. The network consists of 13 collections led by different clinicians throughout the UK. At its heart is an archive infrastructure which manages the DNA and the information associated with it. The European Collection of Cell Cultures in Porton Down handles the blood, peripheral blood lymphocytes and EBV-transformed cell lines, while the Centre for Integrated Genomic Medical Research at Manchester University manages the DNA. These banked samples are available to UK and international researchers, who can examine data and set up collaborative work by registering at the DNA Network's website. The conditions for which samples are currently collected and stored are: Acute leukemia, Asthma and eczema, Late onset Alzheimer's disease, Breast cancer, Colorectal cancer, Coronary artery disease, Glomerulonephritis, Hypertension, Age-related macular degeneration, Multiple sclerosis, Parkinson's disease, Type 2 diabetes, Unipolar depression.
Proper citation: UK DNA Banking Network (RRID:SCR_010619) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 6th, 2022. The biobank comprises paraffin blocks of surgical and autopsy tissue samples and corresponding histological slides as well as cytological material consisting of slides of vaginal smears, fine needle aspiration biopsies and exfoliative cytological material. The tissue samples date back until 1944 and most of the cytological samples until 1970. A subunit of the bank constitutes the National Tissue Microarray Centre. This center is supported by SWEGENE with the purpose to organize and construct tissue microarrays (TMA:s) for high throughput molecular pathology research on various kinds of tumors and other diseases. By linking the TMA.s to long-term and complete clinical follow-up data, prognostic and predictive studies will be facilitated. Biobank content: * Approximately 2,4 million paraffin blocks of surgical tissue specimens, * 1,1 million paraffin blocks of tissue samples from autopsies, * 3,8 million histological slides and * 1,6 million cytology slides. At present, the Tissue Microarray Centre includes: * A consecutive series of all invasive breast cancers (n=600) diagnosed in Malmo between 1988 and 1992. * All incident breast cancers within the Malmo Diet and Cancer cohort (n=400). * A subgroup of 600 pre-menopausal primary breast cancers within the nationwide, population-based randomized tamoxifen trial SBII:2. * 180 primary breast cancers from post-menopausal women included in a similar study. * A set of 120 extremely well characterized primary breast cancer samples with a clinical follow-up of 10 years. More than 40 relevant tumor biological parameters have been recorded in this material and it is therefore useful for a first screening of a marker in order to identify associations to other gene products. * 350 renal cell carcinomas (In collaboration with NUS). We provide researchers with state-of-the-art population based tissue microarrays with long-term and complete follow-up data on survival and treatment. With the TMA-technology, valuable biobank material will be preserved, allowing high throughput in-situ analyses of various tumors and other diseases with a minimal waste of tissue.
Proper citation: UMAS University Hospital - Biobanks of the Department of Clinical Pathology and Cytology (RRID:SCR_005957) Copy
http://purl.bioontology.org/ontology/BCGO
Ontology that assigns a grade to a tumor starting from the 3 criteria of the NGS
Proper citation: Breast Cancer Grading Ontology (RRID:SCR_006658) Copy
Open access resource for human proteins. Used to search for specific genes or proteins or explore different resources, each focusing on particular aspect of the genome-wide analysis of the human proteins: Tissue, Brain, Single Cell, Subcellular, Cancer, Blood, Cell line, Structure and Interaction. Swedish-based program to map all human proteins in cells, tissues, and organs using integration of various omics technologies, including antibody-based imaging, mass spectrometry-based proteomics, transcriptomics, and systems biology. All the data in the knowledge resource is open access to allow scientists both in academia and industry to freely access the data for exploration of the human proteome.
Proper citation: The Human Protein Atlas (RRID:SCR_006710) Copy
GWASrap is a comprehensive web-based bioinformatics tool to systematically support variant representation, annotation and prioritization for data generated from genome-wide association studies (GWAS) and Next Generation Sequencing (NGS). Our web-based framework utilizes state-of-the-art web technologies to maximize user interaction and visualization of the results. For a given SNP dataset with its P-values, GWASrap will first provide a Circos-style plot to visualize any genetic variants at either the genome or chromosome level. The tool then combines different genomic features (SNP/CNV density, disease susceptibility loci, etc.) with comprehensive annotations that give the researcher an intuitive view of the functional significance of the different genomic regions. The detailed statistics of the underlying study are also displayed on the web page, including variant distribution in different functional categories, classic Manhattan plot and QQ plot. Users can perform interactive operations in the Manhattan panel, such as zooming in and out to search regions or markers of interest. The system can also display a comprehensive range of relevant information from variant genetic attributes to nearby genomic elements, such as enhancers or non-coding RNAs. Furthermore, researchers can obtain extensive functional predictions for various features including transcription factor-binding sites, miRNA and miRNA target sites, and their predicted changes caused by the genetic variants. Our system can re-prioritize genetic variants by combining the original statistical value and variant prioritization score based on a simple additive effect equation. Researchers can also re-evaluate the significance of a trait/disease-associated SNP (TAS) using the dynamic linkage disequilibrium (LD) panel or the tree-like network panel. The GWASrap supports input variants in different formats, not only common variants with a dbSNP rs ID but also rare variants from NGS data, which are represented by chromosome and locations. GWASrap provides a range of web services for data retrieving about the annotation information and effect prediction of each variant in dbSNP using the SOAP interface. The WSDL for each service is available in the API tab. Each service returns JSON string including all related information with key/value. GWASrap provides running results about some current published GWAS as well as a category view for each hot disease / trait. The dataset is brought from published database GWAS or curated from literature.
Proper citation: GWASrap (RRID:SCR_013144) Copy
The UMD-BRCA1/BRCA2 databases have been set up in a joined national effort through the network of 16 diagnostic laboratories to provide up-to-date information about mutations of the BRCA1 and BRCA2 genes identified in patients with breast and/or ovarian cancer. These databases currently contain published and unpublished information about the BRCA1/BRCA2 mutations reported in French diagnostic laboratories. This database includes 28 references and 5530 mutations (1440 different mutations and 786 protein variants) The databases of BRCA1 and BRCA2 mutations were built using the Universal Mutation Database tool. For each mutation, information is provided at several levels: * at the gene level: exon and codon number, wild type and mutant codon, mutation event, mutation name and, * at the protein level: wild type and mutant amino acid, binding domain, affected domain. If you want to submit a mutation, please contact R. Lidereau., S. Caputo. or E. Rouleau.
Proper citation: UMD-BRCA1/ BRCA2 databases (RRID:SCR_006128) Copy
http://colt.ccbr.utoronto.ca/cancer/
The COLT-Cancer database is a collection of shRNA dropout signatures profiles, covering ~16000 human genes, and derived from more than 70 Pancreatic, Ovarian and Breast human cancer cell-lines using the microarray detection platform developed in the COLT (CCBR-OICR Lentiviral Technology) facility at the Moffat Lab. All shRNA dropout profiles are freely available through download or queries via this website.
Proper citation: COLT-Cancer (RRID:SCR_006485) Copy
http://gbrowse.csbio.unc.edu/cgi-bin/gb2/gbrowse/slep/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Database of genetic and gene expression data from the published literature on psychiatric disorders. Users can search the accumulated data to find the evidence in support of the involvement of a particular genomic region with a set of important psychiatric disorders, ADHD, autism, bipolar disorder, eating disorder, major depressive disorder, schizophrenia, and smoking behavior. It contains findings from manual reviews of 144 papers in psychiatric genetics, 136 primary reports and 8 meta-analyses. Disorders covered include schizophrenia (44 papers), autism (24 papers), bipolar disorder (24 papers), smoking behavior (24 papers), major depressive disorder and neuroticism (14 papers), ADHD (8 papers), eating disorders (3 papers), and a combined schizophrenia-bipolar phenotype (3 papers). The unbiased searches integrated into SLEP include genomewide linkage (117 papers), genomewide association (15 papers), copy number variation (9 papers), and gene expression studies of post-mortem brain tissue (3 meta-analyses courtesy of the Stanley Foundation). In total, SLEP captures 3,741 findings from these 144 papers. SLEP also contains over 70,000 SignPosts. These annotations derive from many different sources and are designed to try to capture current state of knowledge about disease associations in the human genome. SignPosts can be searched simultaneously with the psychiatric genetics literature in order to integrate these two bodies of knowledge. The SignPosts include: accumulated GWAS findings from the human genetics literature, the OMIM database, candidate gene association study literature, CNV location and frequency data, SNPs that influence gene expression in brain, genes expressed in brain, genes with evidence of imprinting and random monoalleleic expression, genes mutated in breast or colorectal cancer, and pathway data from BioCyc.
Proper citation: Sullivan Lab Evidence Project (RRID:SCR_000753) Copy
http://ranchobiosciences.com/gse20194/
Curated data set of gene expression data from 230 stage I-III breast cancers that were generated from fine needle aspiration specimens of newly diagnosed breast cancers before any therapy. The biopsy specimens were collected sequentially during a prospective pharmacogenomic marker discovery study between 2000 and 2008. These specimens represent 70-90% pure neoplastic cells with minimal stromal contamination. In the study, patients received 6 months of preoperative (neoadjuvant) chemotherapy including paclitaxel, 5-fluorouracil, cyclophosphamide and doxorubicin followed by surgical resection of the cancer.
Proper citation: GSE20194 (RRID:SCR_003645) Copy
http://ranchobiosciences.com/gse1456/
Curated series of expression data for 159 tumors from which RNA could be collected in sufficient amounts and quality for analysis from breast cancer patients. Tissue material was collected from all breast cancer patients receiving surgery at Karolinska Hospital from 1994-1996.
Proper citation: GSE1456 (RRID:SCR_003642) Copy
http://epi.grants.cancer.gov/CFR/
The Breast Cancer Family Registry (Breast CFR) and the Colon Cancer Family Registry (Colon CFR) were established by the National Cancer Institute (NCI) as a unique resource for investigators to use in conducting studies on the genetics and molecular epidemiology of breast and colon cancer. Known collectively as the CFRs, they share a central goal: the translation of research to the clinical and prevention settings for the benefit of Registry participants and the general public. The CFRs are particularly interested in: * Identifying and characterizing cancer susceptibility genes; * Defining gene-gene and gene-environment interactions in cancer etiology; and * Exploring the translational, preventive, and behavioral implications of research findings. The CFRs do not provide funding for studies; however, researchers can apply to access CFR data and biospecimens contributed by thousands of families from across the spectrum of risk for these cancers and from population-based or relative controls. Special features of the CFRs include: * Population-based and clinic-based ascertainment; * Systematic collection of validated family history; * Epidemiologic risk factor , clinical, and followup data; * Biospecimens (including tumor blocks and Epstein-Barr virus (EBV)-transformed cell lines); * Ongoing molecular characterization of the participating families; and * A combined informatics center.
Proper citation: NCI Breast and Colon Cancer Family Registries (RRID:SCR_006664) Copy
http://umanitoba.ca/institutes/manitoba_institute_cell_biology/MBTB/Index4.htm
A collection of tissue and related clinical data for breast cancer. The Bank stores three types of information on each case within a secure location in CancerCare Manitoba. This information relates to the tissue, clinical, and follow-up information. Tissue information includes the composition of the tissue, the size and type of tumor. Clinical information includes the patient age, clinical symptoms and the results of clinical tests such as x-rays. Follow-up information includes the type of treatment after surgery and the response to this treatment. The Bank provides an important resource both for breast cancer research at the University of Manitoba and for researchers across Canada and internationally. Researchers are charged to cover the costs of storage and release but no tissue or information is sold. The Bank has supported over 50 research studies on breast cancer across North America and Europe. Information is never released from the Bank with any label that might allow it to be traced to an individual. Information is only released as part of a set of anonymized cases, where each case is labeled by an anonymous tumor bank number and consists of a section of tissue with related information. Researchers can apply to study these cases only through a review process and if they obtain approval for their research project from an institutional ethics review board. If approved, researchers are provided with tissue sections and the related clinical information from a set of typically 100 or more ����??cases����??. These cases are carefully selected from the computer database on the basis of selection criteria such as size and type of tumor that are relevant to the research question under study. During the assessment of each breast biopsy specimen small tissue samples are taken by Pathologists to process and examine under a microscope and these samples are then stored as a ����??clinical archive����??. After all diagnosis has been completed the Bank organizes these tissues and related clinical data into ����??cases����?? for both future research and future clinical purposes and stores these ����??cases����?? in CancerCare Manitoba. All cases are distinguished by a Tumor Bank number but are anonymous due to the absence of any tag that might allow it to be traced to an individual patient.
Proper citation: Manitoba Breast Tumor Bank (RRID:SCR_008723) Copy
Tissue bank that specifically provides human tissue and cell samples for research purposes. It offers PBMCs, whole blood, solid tumor tissues, circulating tumor cells, and a variety of other bio-specimens.
Proper citation: Conversant Biologics Inc. (RRID:SCR_010675) Copy
http://www.shca.org.cn/english/content/11540
The Institutional Tissue Bank (ITB) of Fudan University Shanghai Cancer Center was established in 2006 with the goal of serving as a central repository for human tissue samples for cancer research and possible personalized medicine for the institution. The Institutional Research Board oversees the fulfilling of informed consent of each patient whose samples are collected. The ITB''s collection procedures meet the global quality standards and provide high quality tissue samples. The quality control for morphology, RNA, DNA and protein has been set up to ensure the sample quality. Routine frozen section from tissue aliquot is made for every piece of sample to ensure the component of tumor tissue and the pathological feature is the same as the diagnosed tumor. Agilent 2100 Bioanalyzer was used to provide RNA and DNA quality parameters. The Tissue Bank occupies 500 m2, with sufficient space for sample preparation and storage, data registration, data tracking/access, related equipments and monitor system. Variant samples including blood, tumor tissue, and body fluids are collected and serve as alternative permanent patient tissue records. Annotation of collected samples is captured through linking the medical record and pathological report system to tissue bank software. Frequent tumor types such as lung cancer, breast cancer, gastric cancer, urological tumors, gynecological tumors and esophageal cancers, head & neck cancers, as well as infrequent cancer types such as malignant soft tissue sarcomas, pancreatic cancer, gall bladder cancer, and other rare cancers are all collected and stored. Tumor tissues are stored with matched normal tissues. Serum and plasma are isolated from coagulation plus and coagulation minus blood samples. White blood cells are stored as well. Tissues are stored both in RNALater at -20 degrees C and -80 degrees C after snap frozen. Samples have been increased from 4,000 in 2008 to 10,783 in 2009. To the end of September 2010, over 30,000 samples has been processed and stored in our tissue bank. As planned, 50,000 samples will be stored dynamically. Over 50 funded projects have used the samples from our tissue bank. Productive papers have been published in the past years by using the samples. More and more projects will be approved to get research resources from tissue bank in the future. The tissue bank of FUSCC has been designated as the key subject and successful model by Shanghai municipal government.
Proper citation: Cancer Center Tissue Bank - Fudan University (RRID:SCR_004596) Copy
Karolinska Mammography Project for Risk Prediction of Breast Cancer. Research group at Karolinska Institutet created the world’s best characterised breast cancer cohort with the aim to reduce mortality and incidence in breast cancer through translational research focusing on breast cancer screening and prevention.
Proper citation: Karma (RRID:SCR_026337) Copy
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